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PyTorch implementations of deep reinforcement learning algorithms and environments

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

Code for Hands On Intelligent Agents with OpenAI Gym book to get started and learn to build deep reinforcement learning agents using PyTorch

Reinforcement learning with PyTorch, inspired by MorvanZhou, change the framework from Tensorflow to PyTorch

Simple Cartpole example writed with pytorch.

A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.

Solutions of assignments of Deep Reinforcement Learning course presented by the University of California, Berkeley (CS285) in Pytorch framework

PyTorch 1.x Reinforcement Learning Cookbook, published by Packt

Basic reinforcement learning algorithms. Including:DQN,Double DQN, Dueling DQN, SARSA, REINFORCE, baseline-REINFORCE, Actor-Critic,DDPG,DDPG for discrete action space, A2C, A3C, TD3, SAC, TRPO

This is a repo for deep reinforcement learning in trading. I used value based double DQN variant for single stock trading. The agent learn to make decision between selling, holding and buying stock with fixed amount based on the reward returned from the environment.